The OT map itself also finds applications, for instance in joint domain adaption or transfer learning [1]}, [2]}, where the goal is to learn in an unsupervised setting the labels of a dataset based on another similar dataset which is labeled.
In single-cell biology [3]}, the optimal transport plan interpolates between two observations of a cell population at two successive time-steps.
In natural language processing [4]}, the input measure of words represents a language embedded in Euclidean spaces using e.g. word2vec [5]}, and assignments are related to translation processes.
